7 papers
A Spatiotemporal Gamma Shot Noise Cox Process
Federico Bassetti, Roberto Casarin, Matteo Iacopini +1
A new discrete-time shot noise Cox process for spatiotemporal data is proposed. The random intensity is driven by a dependent sequence of latent gamma random measures. Some propert…
A Bayesian Dynamic Latent Space Model for Weighted Networks
Roberto Casarin, Matteo Iacopini, Antonio Peruzzi
A new dynamic latent space eigenmodel (LSM) is proposed for weighted temporal networks. The model accommodates integer-valued weights, excess of zeros, time-varying node positions…
Bayesian Markov-Switching Partial Reduced-Rank Regression
Maria F. Pintado, Matteo Iacopini, Luca Rossini +1
Reduced-Rank (RR) regression is a powerful dimensionality reduction technique but it overlooks any possible group configuration among the responses by assuming a low-rank structure…
Static and Dynamic BART for Rank-Order Data
Matteo Iacopini, Eoghan O'Neill, Luca Rossini
Ranking lists are often provided at regular time intervals in a range of applications, including economics, sports, marketing, and politics. Most popular methods for rank-order dat…
A Quantile Nelson-Siegel model
Matteo Iacopini, Aubrey Poon, Luca Rossini +1
We propose a novel framework for modeling the yield curve from a quantile perspective. Building on the dynamic Nelson-Siegel model of Diebold et al. (2006), we extend its tradition…
Bayesian Multivariate Quantile Regression with alternative Time-varying Volatility Specifications
Matteo Iacopini, Francesco Ravazzolo, Luca Rossini
This article proposes a novel Bayesian multivariate quantile regression to forecast the tail behavior of energy commodities, where the homoskedasticity assumption is relaxed to all…